Instructions to use procedure2012/Zephyr-Summarizer-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use procedure2012/Zephyr-Summarizer-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="procedure2012/Zephyr-Summarizer-3B")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("procedure2012/Zephyr-Summarizer-3B") model = AutoModel.from_pretrained("procedure2012/Zephyr-Summarizer-3B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 2,615 Bytes
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license: apache-2.0
library_name: transformers
---
# Zephyr-Summarizer-3B
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<img src="figures/fig1.png" width="60%" alt="Zephyr-Summarizer-3B" />
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## 1. Introduction
Zephyr-Summarizer-3B produces faithful, abstractive summaries across documents, dialogues and transcripts.
<p align="center">
<img width="80%" src="figures/fig3.png">
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## 2. Evaluation Results
### Comprehensive Benchmark Results
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| | Benchmark | BriefLM | Zephyr-1B | Condenser | Zephyr-Summarizer-3B |
|---|---|---|---|---|---|
| **Core Reasoning Tasks** | Math Reasoning | 0.613 | 0.638 | 0.643 | 0.660 |
| | Logical Reasoning | 0.808 | 0.827 | 0.819 | 0.850 |
| | Common Sense | 0.770 | 0.774 | 0.744 | 0.796 |
| **Language Understanding** | Reading Comprehension | 0.736 | 0.770 | 0.744 | 0.776 |
| | Question Answering | 0.604 | 0.639 | 0.632 | 0.664 |
| | Text Classification | 0.806 | 0.797 | 0.793 | 0.850 |
| | Sentiment Analysis | 0.774 | 0.792 | 0.809 | 0.825 |
| **Generation Tasks** | Code Generation | 0.706 | 0.726 | 0.744 | 0.752 |
| | Creative Writing | 0.699 | 0.703 | 0.677 | 0.726 |
| | Dialogue Generation | 0.676 | 0.690 | 0.671 | 0.720 |
| | Summarization | 0.762 | 0.794 | 0.796 | 0.814 |
| **Specialized Capabilities** | Translation | 0.798 | 0.803 | 0.797 | 0.831 |
| | Knowledge Retrieval | 0.695 | 0.699 | 0.673 | 0.732 |
| | Instruction Following | 0.792 | 0.803 | 0.771 | 0.808 |
| | Safety Evaluation | 0.777 | 0.777 | 0.751 | 0.790 |
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### Overall Performance Summary
The Zephyr-Summarizer-3B demonstrates strong performance across all evaluated benchmark categories, with particularly notable results in reasoning and generation tasks.
## 3. Chat Website & API Platform
We offer a chat interface and API for you to interact with Zephyr-Summarizer-3B. Please check our official website for more details.
## 4. How to Run Locally
Please refer to our code repository for more information about running Zephyr-Summarizer-3B locally.
### Temperature
We recommend setting the temperature parameter to 0.6.
## 5. License
This repository is released under the apache-2.0 license. The model supports commercial use.
## 6. Contact
If you have any questions, please contact us at info@zephyr.works.
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